Recombinative Hill-Climbing: A Stronger Search Method for Genetic Progranuning - Hooper - 1997Hooper, D Recombinative Hill-Climbing: A Stronger Search Method for Genetic Programming. In: Koza, J. eds. (1997) Genetic Programming 1997. Morgan-Kaufmann, San Francisco, CA, pp. 174-179...
首先,在Wikipedia中,对Hill climbing的描述是“In numerical analysis, hill climbing is a mathematical optimization technique which belongs to the family of local search. ”(refer to en.wikipedia.org/wiki/H),即 Hill climbing 是在数值分析中一个用于获得局域最优解的算法工具。Hill climbing 本质上是一种...
It uses a hill climbing search technique to reduce the likelihood of the premature convergence. In this paper, a memetic approach is studied for the NP... D Boughaci,H Drias,B Benhamou - IEEE Conference on Cybernetics & Intelligent Systems 被引量: 19发表: 2005年 Characterizing the Behavior...
Since the computational cost to do this work is prohibitive even for problems of moderate sizes, we adopt a genetic algorithm in conjunction with hill climbing search technique to reduce the complexity. Experimental results show that good solutions can be found with lower cost using our method....
β-hill climbing is a recently introduced local search algorithm that is able to effectively solve different optimization problems. β-hill climbing is utilized in the modified HS algorithm as a local search technique to improve the generated solution by HS. Two algorithms are proposed: the first ...
1) hill climbing 爬山策略2) search by hill climbing 用爬山策略搜索3) crawling strategy 爬行策略 1. This paper presents a crawling strategy that can download the pages of Deep Web effectively. 该文提出的Deep Web爬虫爬行策略,可以有效地下载Deep Web页面。 2. Based on analyzing the recent ...
Summary: Enforced hill-climbing is an effective deterministic hill-climbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). We propose and evaluate a stochastic generalization of enforced hill-climbing for online use in goal-oriented probabilistic ...
An adaptive hill climbing method is proposed as the local search technique in the framework of memetic algorithms, which combines the features of greedy crossover-based hill climbing and steepest mutation-based hill climbing. In order to address the convergence problem, two diversity maintaining ...
As we know hill climbing searches are famous for converging to local optimums. Since k-means can converge to a local optimum, different initial points generally lead to different convergence cancroids, which makes it important to start with a reasonable initial partition in order to achieve high...
Search Cart Home Journal of VLSI signal processing systems for signal, image and video technology Article Hill-Climbing, Density-Based Clustering and Equiprobabilistic Topographic MapsPublished: 01 August 2000 Volume 26, pages 79–94, (2000) Cite this article ...